#!/bin/bash

GDAL_TILE_PROCESSES=16
GDAL_TILE_ZOOMS=8-14
GDAL_SAMPLING_WARP=cubic
GDAL_SAMPLING_TILE=antialias

# Create virtual dataset with coordinates
gdal_translate -of VRT -a_srs EPSG:4326 -outsize 300% 300% -gcp 1212.364348591552 6061.248855633805 20.83722246 57.50000587 -gcp 35268.11910211272 1751.296566901392 28.33721426 57.99999998 -gcp 36195.236531690185 18581.370950704215 28.33719148 55.9999718 -gcp 567.4862235915825 18678.75864876759 20.83721486 55.99999728 -gcp 21753.75 2208.1635238656454 25.3372167 58 -gcp 19585.5 19100.029463759573 24.8372167 56 -gcp 14901.75 10684.635238656454 23.8372167 57 NLL215_Latvijas_celu_un_pagastu_robezu_karte_1931-k_001_ktl1-2-82.jpg NLL215_Latvijas_celu_un_pagastu_robezu_karte_1931-k_001_ktl1-2-82.vrt

# Add cutline to VRT
gdalwarp -r $GDAL_SAMPLING_WARP -tps -dstalpha -cutline_srs EPSG:4326 \
  -cutline "POLYGON(($(echo -e "0.0 0.0\n36720.0 0.0\n36720.0 22929.0\n0.0 22929.0" | \
  gdaltransform -tps -output_xy NLL215_Latvijas_celu_un_pagastu_robezu_karte_1931-k_001_ktl1-2-82.vrt | \
  awk 'NR==1{first=$0} {printf "%s %s,", $1,$2} END{print " " first}')))" \
  NLL215_Latvijas_celu_un_pagastu_robezu_karte_1931-k_001_ktl1-2-82.vrt NLL215_Latvijas_celu_un_pagastu_robezu_karte_1931-k_001_ktl1-2-82.cut.vrt

# Generate tiles
gdal2tiles.py -r $GDAL_SAMPLING_TILE --xyz -z $GDAL_TILE_ZOOMS -x --processes=$GDAL_TILE_PROCESSES NLL215_Latvijas_celu_un_pagastu_robezu_karte_1931-k_001_ktl1-2-82.cut.vrt NLL215_Latvijas_celu_un_pagastu_robezu_karte_1931-k_001_ktl1-2-82.xyz